Me and Ben Pace (with some help from Niki Shams) made a Guesstimate model of how much information cascades is costing science in terms of wasted grant money. The model is largely based on the excellent paper “How citation distortions create unfounded authority: analysis of a citation network” (Greenberg, 2009), which traces how an uncertain claim in biomedicine is inflated to established knowledge over a period of 15 years, and used to justify ~$10 million in grant money from the NIH (we calculated the number ourselves here).
There are many open questions about some of the inputs to our model as well as how this generalises outside of academia (or even outside of biomedicine). However, we see this as a “Jellybaby” in Douglas Hubbard’s sense—it’s a first data-point and stab at the problem which brings us from “no idea idea how big or small the costs of info-cascades are”, to at least “it is plausible though very uncertain that the costs can be on the order of magnitude of billions of dollars, yearly, in academic grant money”.
Me and Ben Pace (with some help from Niki Shams) made a Guesstimate model of how much information cascades is costing science in terms of wasted grant money. The model is largely based on the excellent paper “How citation distortions create unfounded authority: analysis of a citation network” (Greenberg, 2009), which traces how an uncertain claim in biomedicine is inflated to established knowledge over a period of 15 years, and used to justify ~$10 million in grant money from the NIH (we calculated the number ourselves here).
There are many open questions about some of the inputs to our model as well as how this generalises outside of academia (or even outside of biomedicine). However, we see this as a “Jellybaby” in Douglas Hubbard’s sense—it’s a first data-point and stab at the problem which brings us from “no idea idea how big or small the costs of info-cascades are”, to at least “it is plausible though very uncertain that the costs can be on the order of magnitude of billions of dollars, yearly, in academic grant money”.